Abstract: An automated method is provided for mitigating data service system performance degradation due to excess user traffic. A traffic assessment and management server (TAMS) retrieves historical time-varying environment information and transaction data for a data service processing system (DSPS). The TAMS receives a set of expected environment conditions for a future time interval and determines, using the time-varying environment and transaction data, estimated traffic information for the DSPS for the future time interval. The estimated traffic information includes an estimated usage level for at least one system component. The TAMS establishes a simulated system configuration for the DSPS and simulates DSPS operation using the estimated traffic information. The TAMS then determines from the simulation, an estimated likelihood of failure for the at least one system component.

Abstract: An object tracking apparatus, method and computer-readable medium for detecting an object from output information of sensors, tracking the object on a basis of a plurality of detection results, generating tracking information of the object represented in a common coordinate system, outputting the tracking information, and detecting the object on a basis of the tracking information.

Abstract: The invention relates to a method for providing a virtual sensor in an automation system of an industrial system. A measurement value of a physical sensor, said measurement value corresponding to a physical parameter of the industrial system, is received in a processing device of the automation system. A data set which has been generated using a simulation model is provided in the processing device, wherein the data set produces a unique relationship between possible measurement values of the physical sensor and corresponding output values of the virtual sensor. The data set and the received measurement value are used to determine which output value of the virtual sensor belongs to the received measurement value (20), and said output value is then displayed on a display device of the industrial system.

Abstract: To determine a quality indicator of production batch-run of a production process, a computer compares time-series with multi-source data from a reference batch-run and time-series with multi-source data from the production batch-run. Before comparing, the computer converts multi-variate time-series to uni-variate time-series, by first multiplying data values of source-specific uni-variate time-series with source-specific factors from a conversion factor vector and second summing up the multiplied data values according to discrete time points. The source-specific factors of the conversion factor vector are obtained earlier by processing reference data, including the determination of characteristic portions of the time-series, converting, aligning by time-warping and evaluating displacement in time between characteristic portions before alignment and after alignment.

Abstract: A textile mill system and associated method include a plurality of spinning mills each having textile machines. A computer system determines adapted machine parameters for the textile machines and processes within the spinning mills. The computer system includes a receiving and transmitting section configured to receive operational information from the spinning mills and the textile machines, and a first database configured to store the received operational information. A processing section includes an optimizer section with a neural network, wherein the neural network uses the operational information stored in the first database with processes for or derived from supervised or unsupervised machine or deep learning to determine the adapted machine parameters.

Abstract: A first robot arm places a calibration object into a load lock that separates a factory interface from a transfer chamber using a first taught position. A second robot arm retrieves the calibration object from the load lock using a second taught position. A controller determines, using a sensor, a first offset amount between a calibration object center of the calibration object and a pocket center of the second robot arm. The controller determines a characteristic error value that represents a misalignment between the first taught position of the first robot arm and the second taught position of the second robot arm based on the first offset amount. The first robot arm or the second robot arm uses the first characteristic error value to compensate for the misalignment for objects transferred between the first robot arm and the second robot arm via the load lock.

Abstract: An apparatus is provided, which includes a setting unit for setting an operation content for a manufacturing system configured to manufacture an object to be manufactured, a first acquisition unit for acquiring a posterior state parameter set indicating a state of at least one of the manufacturing system or the object to be manufactured after the operation content is set, and a learning processing unit for executing, by using learning data including the operation content and the posterior state parameter set, a learning process of a control model of the manufacturing system configured to output the operation content that increases a reward value determined by a preset reward function in response to input of a state parameter set indicating a state of at least one of the manufacturing system or the object to be manufactured.

Abstract: Disclosed are a vehicle access system and method with at least two sets of a receiver and a transmitter, each set configured to receive a type of wireless communication signal from a corresponding transmitter of a user device, and the type of wireless communication signal received by a set is different from that received by at least another set; a signal module communicating with each set, each signal module configured to process the wireless communication signals received from the set to determine an initial location of the user device relative to the vehicle; a localization module communicating with the signal modules and configured to determine a final location of the user device relative to the vehicle, based on the initial locations determined by the signal modules; and a controller configured to lock or unlock a door of the vehicle based on the determined final location of the user device.

Abstract: A controller emulator, coupled to an interface that exposes the controller emulator to inputs from external sources, provides one or more control signals to a process simulator and a deep learning process. In response, the process simulator simulates response data that is provided to the deep learning processor. The deep learning processor generates expected response data and expected behavioral pattern data for the one or more control signals, as well as actual behavioral pattern data for the simulated response data. A comparison of at least one of the simulated response data to the expected response data and the actual behavioral pattern data to the expected behavioral pattern data is performed to determine whether anomalous activity is detected. As a result of detecting anomalous activity, one or more operations are performed to address the anomalous activity.

Abstract: A learning device, for constructing a learning model for generating a prior acceleration command value for controlling a control target in advance of the time a load on a boiler used for thermal power generation changes, includes: a learner configured to generate the learning model by mechanically learning, as learning data, a data set including a power generation command value for the thermal power generation and the prior acceleration command value which have been used in a previous operation of the boiler.

Abstract: A building management system with artificial intelligence based control of a building includes data collectors are configured to receive data and generate data streams for subsystems of the building. The system includes a learning engine configured to identify a building state of the building by correlating data of the data streams for the subsystems and provide the identified building state to cognitive agents. The system includes the cognitive agents, each of the cognitive agents configured to receive the identified building state from the learning engine, generate a control decision based on the received building state, and operate at least one of the plurality of subsystems of the building to control a physical condition of the building based on the control decision.

Abstract: Systems and methods for quantifying saved time during data entry.

Abstract: Aspects of the present disclosure correspond to managing premises by processing input data, such as the appliance's operational and usage profiles and/or individual's health and behavior profile. One aspect of the present disclosure related monitoring aspect based on processing the appliance's operational and usage profiles. For example, the appliance's operational parameters together with sensor data associated with the appliances can be utilized to monitor the premises. Another aspect of the present disclosure related to generating command instructions for the individual (e.g., premise user) based on the individual's health and behavior profile. For example, the usage of the appliances can provide to the individual one or more commanding instructions based on the individual's health and behavior profile.

Abstract: An air-conditioning control system includes an information receiver configured to communicate with a second vehicle around a first vehicle, to acquire drive source information of the second vehicle, and an air-conditioning controller configured to control an air conditioner of the first vehicle in an inside air recirculation mode or in an outside air introduction mode based on the drive source information. The drive source information includes active drive source information indicating a drive source that is currently active in the second vehicle, such that the air conditioner is controlled in accordance with the active drive source.

Abstract: A fraudulent diagnostic machine detection apparatus capable of preventing the occurrence of fraudulent processing due to a fraudulent diagnostic machine being connected in parallel with a legitimate diagnostic machine is a fraudulent diagnostic machine detection apparatus comprising node ECUs of a diagnosis target connected to a communication line and a gateway connected between the communication line and a diagnostic machine connection coupler, wherein the gateway detects an electrical circuit change caused by a pin connection of the diagnostic machine connection coupler being branched and the plurality of diagnostic machines being connected in parallel.

Abstract: An apparatus control device includes: at least one processor; and at least one first memory that stores a program executed by the processor, in which the processor acquires input data based on at least one of acceleration and angular velocity generated by application of an external force to an apparatus, classifies a plurality of the acquired input data into a plurality of clusters by an unsupervised clustering method, acquires relationship data representing relationship between the acquired input data and the plurality of classified clusters, and controls movement of the apparatus based on the acquired relationship data.

Abstract: A power management apparatus 20 comprises: a plurality of energy harvesting input channels 21-24; a first energy storage element connection for connecting to an energy storage element 32; an inductor connection 27; and a switching circuit 28. A controller 30 operates the switching circuit to transfer energy between the energy harvesting input channels 21-24 and the first energy storage element connection 25 by a sequence of energy transfer cycles. Each energy harvesting input channel 21-24 is allocated a plurality of the energy transfer cycles. The controller 30 determines operating parameters for operating the switching circuit 28 which transfer a maximum power from the electrical energy harvesting source connected to the energy harvesting input channel and a maximum power inductor utilisation factor. The controller 30 determines a set of adjusted operating parameters for sharing use of the inductor between the plurality of energy harvesting input channels 21-24.

Abstract: According to some embodiments, a surrogate model creation computer system includes a user interface to interact with a subject matter expert to create a scripted physics-based model workflow associated with an industrial asset. The surrogate model creation computer system further includes a surrogate model creation engine to automatically execute the scripted physics-based model workflow, in connection with a physics-based model of the industrial asset, to generate at least one response surface of the physics-based model workflow. The surrogate model creation engine may then use the response surface and a machine learning process to automatically create a surrogate model of the industrial asset. It may then be arranged to output the surrogate model for use by a substantially real-time analytics package associated with the industrial asset. According to some embodiments, scripting for a physics-based model workflow may also be automatically created.

Abstract: Layout to reduce current crowding at endpoints. At least one example is a semiconductor device comprising: an emitter region defining an inner boundary in the shape of an obround with parallel sides, and the obround having hemispherical ends each having a radius; a base region having a first end, a second end opposite the first end, and base length, the base region disposed within the obround with the base length parallel to and centered between the parallel sides, the first end spaced apart from the first hemispherical end by a first gap greater than the radius, and the second end spaced apart from the second hemispherical ends by a second gap greater than the radius.

Abstract: An apparatus for combustion optimization is provided. The apparatus for combustion optimization includes a management layer configured to collect currently measured real-time data for boiler combustion, and to determine whether to perform combustion optimization and whether to tune a combustion model and a combustion controller by analyzing the collected real-time data, a data layer configured to derive learning data necessary for designing the combustion model and the combustion controller from the real-time data and previously measured past data for the boiler combustion, a model layer configured to generate the combustion model and the combustion controller through the learning data, and an optimal layer configured to calculate a target value for the combustion optimization by using the combustion model and the combustion controller, and to output a control signal according to the calculated target value.

Abstract: A method and a computing apparatus for managing a portfolio of securities and derivatives are provided. The method includes: identifying a plurality of potential trades based on the portfolio of securities and derivatives; obtaining historical market data that relates to the identified plurality of potential trades; assessing a respective optimal value of each of the at least one security that relates to a corresponding one of the potential trades; and determining trades to be executed from among the identified plurality of potential trades. The assessments of the respective optimal values are based on the obtained historical market data, and also on additional information that relates to each security, using statistical methods. The determination of trades to be executed is based on the corresponding optimal values.

Abstract: Predicting weather radar images by building a first machine learning model to generate first predictive radar images based upon input weather forecast data, and a second machine learning model to generate second predictive radar images based upon historical radar images and the first predictive radar images. Further by generating enhanced predictive radar images by providing the first machine learning model weather forecast data for a location and time and providing the second machine learning model with historical radar images for the location and an output of the first machine learning model.

Abstract: A cloud-based performance enhancement service captures and collects data relating to interactions of users with industrial automation systems of multiple industrial customers for storage and analysis on a cloud platform.

Abstract: A controller emulator, coupled to an interface that exposes the controller emulator to inputs from external sources, provides one or more control signals to a process simulator and a deep learning process. In response, the process simulator simulates response data that is provided to the deep learning processor. The deep learning processor generates expected response data and expected behavioral pattern data for the one or more control signals, as well as actual behavioral pattern data for the simulated response data. A comparison of at least one of the simulated response data to the expected response data and the actual behavioral pattern data to the expected behavioral pattern data is performed to determine whether anomalous activity is detected. As a result of detecting anomalous activity, one or more operations are performed to address the anomalous activity.

Abstract: An apparatus, methods and systems for data collection in an industrial environment are disclosed. A monitoring system can include a data collector coupled to a plurality of sensors to collect data, a data storage structured to store a plurality of data collection management plans, a data acquisition circuit structured to interpret a plurality of detection values from the collected data, and a data analysis circuit structured to analyze the collected data and select one of the plurality of data collection management plans, wherein the selected one of the plurality of data collection management plans is selected is at least in part based on a data analysis of received data from the plurality of sensors.

Abstract: A product state estimation device includes: an examination result acquisition device that acquires an examination result related to a state of a product obtained through each shot by a die-casting machine; a time series data acquisition device that acquires time series data based on an output from a sensor that detects an operation state of the die-casting machine at each shot; a time series data manipulation device that performs manipulation that clips data of a predetermined time interval out of the time series data; an estimation model generation device that generates an estimation model by using a neural network with the examination result of the product and the manipulated time series data as learning data; and an estimation device that estimates information related to quality of the product based on the manipulated time series data obtained from a plurality of detection signals at each shot by using the estimation model.

Abstract: The present disclosure relates to a method, device and computer program product for managing jobs in a processing system. The processing system comprises multiple client devices. In the method, based on a group of jobs from the multiple client devices, a current workload of the group of jobs is determined. A group of job descriptions associated with the group of jobs is determined based on configuration information of various jobs in the group of jobs. A future workload associated with the group of jobs is determined based on associations, comprised in a workload model, between job descriptions and future workloads associated with the job descriptions. The group of jobs in the processing system are managed based on the current workload and the future workload. With the foregoing example implementation, jobs in the processing system may be managed more effectively, and latency in processing jobs may be reduced.

Abstract: Methods and systems for generating a semantically augmented image are disclosed. An embedding is generated for each object label associated with a segmented input image. For each embedding associated with a respective object label, a similarity score is computed between the embedding associated with the object label and an embedding representing an object class in an object bank storing a plurality of object images. At least one object is selected, the selected object being associated with a respective object image in the object bank, the selected at least one object being from an identified object class that is identified as contextually relevant to at least one object label associated with the segmented input image, based at least on the similarity score. The selected object is added into the segmented input image to generate the augmented image.

Abstract: Over the past several decades, rapid advances in semiconductors, automation, and control systems have resulted in the adoption of programmable logic controllers (PLCs) in an immense variety of environments. Machine learning techniques help train replacement PLCs when a legacy PLC must be replaced, e.g., due to aging or failure. The techniques facilitate the efficient adoption and correct operation of replacement PLCs in the industrial environment.

Abstract: The present disclosure describes a system and method for improving the way computing devices execute genetic algorithms. A fuzzy logic controller takes various properties of the genetic algorithm (such as the diversity of the population, the performance history of the algorithm in terms of time-efficiency and/or effectiveness at improving the best fitness function results, and available computing resources) to dynamically manage the parameters of the genetic algorithm. In some embodiments, the fuzzy inference system that provides parameters to the genetic algorithm is itself controlled by another fuzzy inference system.

Abstract: Solutions for automated labeling of child objects within tagged parents include: receiving a plurality of parent objects, each having a tag and including a plurality of child objects; receiving a machine learning (ML) component operable to rank objects according to relevance to queries; for each parent object: generating a set of restricted objects, wherein each restricted object corresponds to each child object in the plurality of child objects; for each of a plurality of queries, ranking, with the ML component, the restricted objects according to relevance; based at least on the query and an inverse of the rank of the restricted objects, assigning a child object label.

Abstract: This learning device provides a learned model to an adjuster containing a learned model learned to output a predetermined compensation amount to a controller, in a control system including the controller outputting a command value obtained by compensating a target value based on a compensation amount and a control object controlled to process an object to be processed. The learning device includes: an evaluation part obtaining operation data including the target value, command value and control variable and evaluates the quality of the control variable; a learning part generating candidate compensation amounts based on the operation data, and learning, as teacher data, the generated candidate compensation amount and the specific parameter of the object, and generating a learned model; and a setting part providing the learned model to the adjuster if the evaluated quality is within an allowable range.

Abstract: Disclosed herein are representative embodiments of methods, apparatus, and systems for facilitating operation and control of a resource distribution system (such as a power grid). For example, embodiments of the disclosed technology can be used to improve the resiliency of a power grid and to allow for improved consumption of renewable resources. Further, certain implementations facilitate a degree of decentralized operations not available elsewhere.

Abstract: A fatigue test apparatus includes a control system configured to receive, during a first iteration of a fatigue test of an article under test, a command signal corresponding to a particular test step of the fatigue test. The control system is configured to generate, based on the command signal and during the first iteration, a test output signal to cause a force to be applied to the article under test. The control system is configured to generate an error signal associated with the particular test step during the first iteration. A gain calculation device is configured to generate, based on the error signal, a gain adjustment value associated with the particular test step. A variable gain feedforward device is configured to provide, during a second iteration of the fatigue test and based on the gain adjustment value, a stabilization gain to the control system.

Abstract: Provided are a power supply circuit and a motor control device configured to suppress complexity in management of the power supply circuit. A switching unit acquires identification information that is information corresponding to a type of a torque sensor. Based on the acquired identification information, the switching unit outputs either a reference voltage or a power supply voltage as a standard voltage. A voltage application unit applies to the torque sensor an operation voltage in accordance with a type of the torque sensor based on the power supply voltage or the reference voltage that is the standard voltage of the voltage application unit and that is applied by the switching unit.

Abstract: Computer implemented method for detecting a hand gesture of a user, comprising: (a) Receiving sequential logic models each representing a hand gesture. The sequential logic model maps pre-defined hand poses and motions each represented by a hand features record defined by discrete hand values each indicating a state of respective hand feature. (b) Receiving a runtime sequence of runtime hand datasets each defined by discrete hand values scores indicating current state hand features of a user's moving hand which are inferred by analyzing timed images depicting the moving hand. (c) Submitting the runtime hand datasets and the pre-defined hand features records in SSVM functions to generate estimation terms for the runtime hand datasets with respect to the hand features records. (d) Estimating which of the hand gestures best matches the runtime sequence depicted in the timed images by optimizing score functions using the estimation terms for the runtime hand datasets.

Abstract: Solutions for automated labeling of child objects within tagged parents include: receiving a plurality of parent objects, each having a tag and including a plurality of child objects; receiving a machine learning (ML) component operable to rank the parent objects; for each parent object: generating a set of restricted objects, wherein each restricted object is missing a child object; for each of a plurality of queries, ranking, with the ML component, the restricted objects according to relevance; based at least on the query and an inverse of the rank of the restricted objects, assigning a child object label. In some examples, the object missing from the restricted object having the lowest relevance rank is assigned a label based on the query. Various advantageous uses of the assigned child labels include enhancing search result reporting, automatically generating ML training data, and automatically generating and/or modifying reports.

Abstract: An intelligent regulation system for a mechanical seal, the system comprising: a monitoring device for measuring a signal correlated with a seal in real time; a control device, comprising a state determination module, a feasible region analysis module, an evaluation module and an optimizing module, wherein the state determination module unscrambles the signal obtained by the monitoring device to estimate the state of the seal; the feasible region analysis module determines, according to a current state, a state that the seal can reach by means of the regulating effect of a regulating device; the evaluation module evaluates a value for the state of the seal; and the optimizing module searches a feasible region, where the seal is regulated, for a regulating method with a relatively high value to the greatest extent, and accordingly sends an instruction to the regulating device; and the regulating device for actively applying an action to the seal according to the instruction given by the control device.

Abstract: A computer-implemented method includes receiving, by a processor, real time operation data related to an application, identifying components of the application based on the operation data, extracting relationships and interdependencies between the components, and generating a graph of the identified components, the relationships and the interdependencies. The method also includes determining one or more dynamic metrics of the identified components, the one or more dynamic metrics indicative of interactions between the components, extracting statistical information describing at least one of performance and resource consumption based on the operation data, incorporating the dynamic metrics into the graph, determining a behavior of at least one component based on a pattern of appearance of the at least one component in the graph, and generating a model of the application based on the identified components and the determined behaviors.

Abstract: Systems, methods, and software to facilitate visualization of an application associated with an industrial automation environment are disclosed herein. In at least one implementation, a graphical user interface to the application having a plurality of key performance indicators (KPIs) is rendered. A selection of at least one KPI of the plurality of KPIs is received along with instructions to link the at least one KPI to a home screen of an operating system. Dynamic KPI data associated with the at least one KPI is fed to the operating system for visualization of the at least one KPI on the home screen.

Abstract: Methods and systems may be used for transfer learning of neural networks. According to one example, a method includes: grouping data objects of a first training set into a plurality of clusters; training a base model using a first cluster of the plurality of clusters, the base model being a neural network having a plurality of nodes; generalizing the base model to obtain a generalized base model, the generalizing the base model including setting a portion of the plurality of nodes to have random or predetermined weights; determining that the first cluster is, out of the plurality clusters, most similar to a second training set; and training the generalized base model using the second training set to obtain a trained model.

Abstract: A method for controlling an actuator of a terminal unit in a climate control system includes, in a calibration mode: applying a range of drive signals to the actuator; determining a range of terminal unit capacities over the range of drive signals; and generating a model relating the range of terminal unit capacities to the range of drive signals.

Abstract: An industrial automation system may include an automation device and a control system. The control system may be communicatively coupled to the automation device and may include a first module that may receive a request for information regarding the automation device. The first module may then determine information related to the request for information based on one or more datasets locally available to the first module, alter the information based on a signal configured to obscure the information, and send encrypted information to a second module of the plurality of modules.

Abstract: A system for determining a processing procedure including a plurality of processes for controlling an object, the system includes a learning unit for performing a learning process for determining a processing condition of each of a plurality of processes, and the learning unit acquires a physical quantity correlating with a state of the object on which a process has been performed under a predetermined processing condition, from a device for controlling the object on the basis of the processing procedure, calculates a pseudo state corresponding to the state of the object on the basis of the physical quantity, performs a learning process using a value function, and determines a processing condition of each of the plurality of processes to achieve a target state of the object.

Abstract: A system and a method for determining the parameters of a controller for a controlled system, wherein a simulation model for the controlled system is identified based on detected input and output signals of the controlled system, where parameters of a master controller and a sequence controller used in a pilot control process for the controlled system are automatically defined based on model-based design methods for a controller designed as a model sequence controller, where the behaviour of the closed-loop system can be further improved via a subsequent optimization method, such that the controller can be advantageously designed without any particular control engineering expertise, and thus the frequency of use for model sequence controllers, with their many advantages, can be significantly increased in practical applications.

Abstract: A three dimensional (3D) content generating apparatus includes an inputter configured to receive a plurality of images of an object captured from different locations; a detector configured to identify the object and detect a predetermined feature point of the object from each of the plurality of images; a map former configured to extract 3D location information of the detected feature point, and configured to form at least one depth map with respect to a surface of the object based on the extracted 3D location information of the feature point; and a content generator configured to generate a 3D content of the object using the at least one depth map and the plurality of images.

Abstract: A machine learning device acquires, as a label, a command output by a servo control apparatus to a control target device so as to drive and control the control target device. The machine learning device acquires, as input data, an output of the control target device driven based on the command, and constructs a learning model relating to feedforward control for correcting the command, by performing supervised learning by use of a set of the label and the input data serving as teaching data.

Abstract: System, device, and method of multi-path wireless communication. A method includes: constructing in an electronic device of a user, a control message indicating a user command intended to be performed by a Home Automation Device (HAD) of the user; wherein the constructing includes inserting into the control message a unique Message-Identifier. The method then transmits the control message, from the electronic device of the user to the HAD, concurrently via at least two different wireless communications channels which include at least: (i) a first wireless communication channel that includes passage of traffic through the Internet, and (ii) a second wireless communication channel in which no traffic passes through the Internet.

Abstract: A computer-implemented method for labeling images includes capturing, using an augmented-reality enabled device, a first set of images that include views of a first object; at the augmented-reality enabled device, for each of the first set of images, identifying the first object and generating a bounding box that is associated with the first object; receiving an input providing a first label for the first object; and at the augmented-reality enabled device, for each of at least some of the first set of images, associating the first label with the first object bound by the bounding box.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for presence determination. Systems can include one or more user devices and terminal devices. A current location may be determined of a user that is associated with a particular space of a plurality of different spaces. A plurality of location results may be calculated, wherein each location result is computed using a distinct process of a plurality of processes; and evaluating the plurality of location results to determine a current space of the user; wherein the determining is performed by one or more of, a particular user device, a terminal device, or a server system.